I'm trying to combine to arrays that are wrapped in an Option:
val a = Option(Array(1, 2, 3))
val b = Option(Array(4,5))
val q = for {
x <- a
y <- b
} yield x ++ y
The problem is that if b is None it returns None even though I'd like to have a. And if a is None the compiler complains that ++ is not a member of Nothing (even though I expect to receive b). Is this doable with the standard library or do I have to look at semigroups in Cats or Scalaz?
I tried the following in Cats but couldn't get it to work:
Semigroup[Option[Array[Int]]].combine(a,b) // === a |+| b
It tells me that:
could not find implicit value for parameter ev: cats.kernel.Semigroup[Option[Array[Int]]]
The resulting type should be the same as the types of a and b.
(a ++ b).flatten.toArray
The ++ method is not a part of the Option class, but it works here because of an implicit conversion. If you see the scala doc for Option, it says This member is added by an implicit conversion from Option[A] to Iterable[A] performed by method option2Iterable in scala.Option.
So, options can be treated as iterables.
Preserving the type Option[C[X]], where C is some collection type and X is the element type of that collection, I came up with:
a.fold(b)(x => b.fold(a)(y => Option(x ++ y)))
You should be able to do
val q = a.toList.flatten ++ b.toList.flatten
Related
I have created an immutable list and try to fold it to a map, where each element is mapped to a constant string "abc". I do it for practice.
While I do that, I am getting an error. I am not sure why the map (here, e1 which has mutable map type) is converted to Any.
val l = collection.immutable.List(1,2,3,4)
l.fold (collection.mutable.Map[Int,String]()) ( (e1,e2) => e1 += (e2,"abc") )
l.fold (collection.mutable.Map[Int,String]()) ( (e1,e2) => e1 += (e2,"abc") )
<console>:13: error: value += is not a member of Any
Expression does not convert to assignment because receiver is not assignable.
l.fold (collection.mutable.Map[Int,String]()) ( (e1,e2) => e1 += (e2,"abc") )
At least three different problem sources here:
Map[...] is not a supertype of Int, so you probably want foldLeft, not fold (the fold acts more like the "banana brackets", it expects the first argument to act like some kind of "zero", and the binary operation as some kind of "addition" - this does not apply to mutable maps and integers).
The binary operation must return something, both for fold and foldLeft. In this case, you probably want to return the modified map. This is why you need ; m (last expression is what gets returned from the closure).
The m += (k, v) is not what you think it is. It attempts to invoke a method += with two separate arguments. What you need is to invoke it with a single pair. Try m += ((k, v)) instead (yes, those problems with arity are annoying).
Putting it all together:
l.foldLeft(collection.mutable.Map[Int, String]()){ (m, e) => m += ((e, "abc")); m }
But since you are using a mutable map anyway:
val l = (1 to 4).toList
val m = collection.mutable.Map[Int, String]()
for (e <- l) m(e) = "abc"
This looks arguably clearer to me, to be honest. In a foldLeft, I wouldn't expect the map to be mutated.
Folding is all about combining a sequence of input elements into a single output element. The output and input elements should have the same types in Scala. Here is the definition of fold:
def fold[A1 >: A](z: A1)(op: (A1, A1) => A1): A1
In your case type A1 is Int, but output element (sum type) is mutable.Map. So if you want to build a Map throug iteration, then you can use foldLeft or any other alternatives where you can use different input and output types. Here is the definition of foldLeft:
def foldLeft[B](z: B)(op: (B, A) => B): B
Solution:
val l = collection.immutable.List(1, 2, 3, 4)
l.foldLeft(collection.immutable.Map.empty[Int, String]) { (e1, e2) =>
e1 + (e2 -> "abc")
}
Note: I'm not using a mutabe Map
When I have one Option[T] instance it is quite easy to perform any operation on T using monadic operations such as map() and flatMap(). This way I don't have to do checks to see whether it is defined or empty, and chain operations together to ultimately get an Option[R] for the result R.
My difficulty is whether there is a similar elegant way to perform functions on two Option[T] instances.
Lets take a simple example where I have two vals, x and y of type Option[Int]. And I want to get the maximum of them if they are both defined, or the one that is defined if only one is defined, and None if none are defined.
How would one write this elegantly without involving lots of isDefined checks inside the map() of the first Option?
You can use something like this:
def optMax(op1:Option[Int], op2: Option[Int]) = op1 ++ op2 match {
case Nil => None
case list => list.max
}
Or one much better:
def f(vars: Option[Int]*) = (for( vs <- vars) yield vs).max
#jwvh,thanks for a good improvement:
def f(vars: Option[Int]*) = vars.max
Usually, you'll want to do something if both values are defined.
In that case, you could use a for-comprehension:
val aOpt: Option[Int] = getIntOpt
val bOpt: Option[Int] = getIntOpt
val maxOpt: Option[Int] =
for {
a <- aOpt
b <- bOpt
} yield max(a, b)
Now, the problem you described is not as common. You want to do something if both values are defined, but you also want to retrieve the value of an option if only one of them is defined.
I would just use the for-comprehension above, and then chain two calls to orElse to provide alternative values if maxOpt turns out to be None.
maxOpt orElse aOpt orElse bOpt
orElse's signature:
def orElse[B >: A](alternative: ⇒ Option[B]): Option[B]
Here's another fwiw:
import scala.util.Try
def maxOpt (a:Option[Int]*)= Try(a.flatten.max).toOption
It works with n arguments (including zero arguments).
Pattern matching would allow something easy to grasp, but that might not be the most elegant way:
def maxOpt[T](optA: Option[T], optB: Option[T])(implicit f: (T, T) => T): Option[T] = (optA, optB) match {
case (Some(a), Some(b)) => Some(f(a, b))
case (None, Some(b)) => Some(b)
case (Some(a), None) => Some(a)
case (None, None) => None
}
You end up with something like:
scala> maxOpt(Some(1), None)(Math.max)
res2: Option[Int] = Some(1)
Once you have that building, block, you can use it inside for-comp or monadic operations.
To get maxOpt, you can also use an applicative, which using Scalaz would look like (aOpt |#| bOpt) { max(_, _) } & then chain orElses as #dcastro suggested.
I assume you expect Some[Int]|None as a result, not Int|None (otherwise return type has to be Any):
def maxOption(opts: Option[Int]*) = {
val flattened = opts.flatten
flattened.headOption.map { _ => flattened.max }
}
Actually, Scala already gives you this ability more or less directly.
scala> import Ordering.Implicits._
import Ordering.Implicits._
scala> val (a,b,n:Option[Int]) = (Option(4), Option(9), None)
a: Option[Int] = Some(4)
b: Option[Int] = Some(9)
n: Option[Int] = None
scala> a max b
res60: Option[Int] = Some(9)
scala> a max n
res61: Option[Int] = Some(4)
scala> n max b
res62: Option[Int] = Some(9)
scala> n max n
res63: Option[Int] = None
A Haskell-ish take on this question is to observe that the following operations:
max, min :: Ord a => a -> a -> a
max a b = if a < b then b else a
min a b = if a < b then a else b
...are associative:
max a (max b c) == max (max a b) c
min a (min b c) == min (min a b) c
As such, any type Ord a => a together with either of these operations is a semigroup, a concept for which reusable abstractions can be built.
And you're dealing with Maybe (Haskell for "option"), which adds a generic "neutral" element to the base a type (you want max Nothing x == x to hold as a law). This takes you into monoids, which are a subtype of semigroups.
The Haskell semigroups library provides a Semigroup type class and two wrapper types, Max and Min, that generically implement the corresponding behaviors.
Since we're dealing with Maybe, in terms of that library the type that captures the semantics you want is Option (Max a)—a monoid that has the same binary operation as the Max semigroup, and uses Nothing as the identity element. So then the function simply becomes:
maxOpt :: Ord a => Option (Max a) -> Option (Max a) -> Option (Max a)
maxOpt a b = a <> b
...which since it's just the <> operator for Option (Max a) is not worth writing. You also gain all the other utility functions and classes that work on Semigroup and Monoid, so for example to find the maximum element of a [Option (Max a)] you'd just use the mconcat function.
The scalaz library comes with a Semigroup and a Monoid trait, as well as Max, Min, MaxVal and MinVal tags that implement those traits, so in fact the stuff that I've demonstrated here in Haskell exists in scalaz as well.
Alright, Scala has me feeling pretty dense. I'm finding the docs pretty impenetrable -- and worse, you can't Google the term "Scala ++:" because Google drops the operator terms!
I was reading some code and saw this line:
Seq(file) ++: children.flatMap(walkTree(_))
But couldn't figure it out. The docs for Seq show three things:
++
++:
++:
Where the latter two are over loaded to do.. something. The actual explanation in the doc says that they do the same thing as ++. Namely, add one list to another.
So, what exactly is the difference between the operators..?
++ and ++: return different results when the operands are different types of collection. ++ returns the same collection type as the left side, and ++: returns the same collection type as the right side:
scala> List(5) ++ Vector(5)
res2: List[Int] = List(5, 5)
scala> List(5) ++: Vector(5)
res3: scala.collection.immutable.Vector[Int] = Vector(5, 5)
There are two overloaded versions of ++: solely for implementation reasons. ++: needs to be able to take any TraversableOnce, but an overloaded version is provided for Traversable (a subtype of TraversableOnce) for efficiency.
Just to make sure:
A colon (:) in the end of a method name makes the call upside-down.
Let's make two methods and see what's gonna happen:
object Test {
def ~(i: Int) = null
def ~:(i: Int) = null //putting ":" in the tail!
this ~ 1 //compiled
1 ~: this //compiled
this.~(1) //compiled
this.~:(1) //compiled.. lol
this ~: 1 //error
1 ~ this //error
}
So, in seq1 ++: seq2, ++: is actually the seq2's method.
edited: As #okiharaherbst mentions, this is called as right associativity.
Scala function naming will look cryptic unless you learn a few simple rules and their precedence.
In this case, a colon means that the function has right associativity as opposed to the more usual left associativity that you see in imperative languages.
So ++: as in List(10) ++: Vector(10) is not an operator on the list but a function called on the vector even if it appears on its left hand-side, i.e., it is the same as Vector(10).++:(List(10)) and returns a vector.
++ as in List(10) ++ Vector(10) is now function called on the list (left associativity), i.e., it is the same as List(10).++(Vector(10)) and returns a list.
what exactly is the difference between the operators..?
The kind of list a Seq.++ operates on.
def ++[B](that: GenTraversableOnce[B]): Seq[B]
def ++:[B >: A, That](that: Traversable[B])(implicit bf: CanBuildFrom[Seq[A], B, That]): That
def ++:[B](that: TraversableOnce[B]): Seq[B]
As commented in "What is the basic collection type in Scala?"
Traversable extends TraversableOnce (which unites Iterator and Traversable), and
TraversableOnce extends GenTraversableOnce (which units the sequential collections and the parallel.)
i tried
type ?[_] = Option[_]
def f(x: ?[Int]) = for (y <- x) yield y
(but i don't know what i am doing.)
insofar as types are just objects, i should be able to define a postix operator (i.e. zero arity method) for use in type signatures (i think). it might need a space like
def f(x: Int ?) = for (y <- x) yield y
scala makes it easy to use the Option type with matching and polymorphism, avoid null. but, most classes are (nullable) vars and java often returns vars. using classes and calling java are two of scala's selling points. an easy-to-write and easy-to-read syntax would support Options even more strongly.
what are all the things that scala does with "?" that make its parsing special.
ideally, one could write
def f(x: Int?) = for (y <- x) yield y
like other languages. can we do this in scala (without a macro)?
First, types are not objects. In fact, Scala has exactly two namespaces: values and types. They are very different things, and play by very different rules.
The postfix idea is kind of nice, actually, but it is not possible. There's an infix notation for types, though.
Now, to what you wrote:
type ?[_] = Option[_]
Each underscore has a different meaning. The underscore in ?[_] means ? is higher-kinded, but you don't care what it's type parameter is. The underscore in Option[_] means Option is an existential type. So when you write x: ?[Int], Scala will convert it to x: Option[t] { forSome type t }. This means that not only you don't get the Int, but the type parameter of Option is unknowable (you just know it exists).
However, it does compile:
scala> def f(x: ?[Int]) = for (y <- x) yield y
f: (x: ?[Int])Option[Any]
Which version of Scala did you use? 2.11? A co-worker of mine has already found some type inference regressions on 2.11, so that could be it.
The proper way to write the type alias would be this:
type ?[+A] = Option[A]
Not only we pass the type parameter along (it is a parameter, after all!), but we need to specify co-variance for it to act just Option (which is co-variant itself).
Now, as to your two questions, Scala has absolutely no special treatment of ?. And, no, you can't do this. This ? is not exactly widespread among languages either, and in all of them that support it, it is built in the language, and not something externally defined.
Besides, it's kind of a joke that, when interface with Java, typing out Option would be a problem -- not with the average identifier size in Java!
You intended to get an Option[Int] out:
scala> type ?[A] = Option[A]
defined type alias $qmark
scala> def f(x: ?[Int]) = for (y <- x) yield y + 1
f: (x: ?[Int])Option[Int]
and it does compile anyway.
You could maybe
scala> type ?[A,_] = Option[A]
defined type alias $qmark
scala> def f(x: Int ? _) = for (y <- x) yield y + 1
f: (x: ?[Int, _])Option[Int]
or similar.
scala> def f(x: Int ?_) = for (y <- x) yield y + 1
f: (x: ?[Int, _])Option[Int]
looks more postfixy.
P.S. Still curious whether variance annotation on type alias is required or merely advisable.
scala> type ?[A] = Option[A]
defined type alias $qmark
scala> trait X ; trait Y extends X ; trait Z extends X
defined trait X
defined trait Y
defined trait Z
scala> val x: ?[X] = null.asInstanceOf[?[Y]] // why is this OK?
x: ?[X] = null
scala> class C[A]
defined class C
scala> val c: C[X] = null.asInstanceOf[C[Y]] // like this is not OK
<console>:10: error: type mismatch;
found : C[Y]
required: C[X]
Note: Y <: X, but class C is invariant in type A.
You may wish to define A as +A instead. (SLS 4.5)
val c: C[X] = null.asInstanceOf[C[Y]]
^
Maybe compare SI-8522 and related issues.
You might consider a renaming import. When you create a type alias you only rename a type. When you rename a symbol during import you include all referents of that name, both type and value.
To wit:
scala> import scala.{Option => ?}
import scala.{Option=>$qmark}
scala> val oi1: ?[Int] = Some(1)
oi1: Option[Int] = Some(1)
scala> def mi1(oi: ?[Int]): Int = oi.getOrElse(-1)
mi1: (oi: Option[Int])Int
scala> mi1(None)
res1: Int = -1
scala> mi1(?(1))
res2: Int = 1
Compare with this:
scala> type ?[A] = Option[A]
scala> def mi1(oi: ?[Int]): Int = oi.getOrElse(-1)
mi1: (oi: ?[Int])Int
scala> mi1(?(1))
<console>:10: error: not found: value ?
mi1(?(1))
^
In scala, how do I define addition over two Option arguments? Just to be specific, let's say they're wrappers for Int types (I'm actually working with maps of doubles but this example is simpler).
I tried the following but it just gives me an error:
def addOpt(a:Option[Int], b:Option[Int]) = {
a match {
case Some(x) => x.get
case None => 0
} + b match {
case Some(y) => y.get
case None => 0
}
}
Edited to add:
In my actual problem, I'm adding two maps which are standins for sparse vectors. So the None case returns Map[Int, Double] and the + is actually a ++ (with the tweak at stackoverflow.com/a/7080321/614684)
Monoids
You might find life becomes a lot easier when you realize that you can stand on the shoulders of giants and take advantage of common abstractions and the libraries built to use them. To this end, this question is basically about dealing with
monoids (see related questions below for more about this) and the library in question is called scalaz.
Using scalaz FP, this is just:
def add(a: Option[Int], b: Option[Int]) = ~(a |+| b)
What is more this works on any monoid M:
def add[M: Monoid](a: Option[M], b: Option[M]) = ~(a |+| b)
Even more usefully, it works on any number of them placed inside a Foldable container:
def add[M: Monoid, F: Foldable](as: F[Option[M]]) = ~as.asMA.sum
Note that some rather useful monoids, aside from the obvious Int, String, Boolean are:
Map[A, B: Monoid]
A => (B: Monoid)
Option[A: Monoid]
In fact, it's barely worth the bother of extracting your own method:
scala> some(some(some(1))) #:: some(some(some(2))) #:: Stream.empty
res0: scala.collection.immutable.Stream[Option[Option[Option[Int]]]] = Stream(Some(Some(Some(1))), ?)
scala> ~res0.asMA.sum
res1: Option[Option[Int]] = Some(Some(3))
Some related questions
Q. What is a monoid?
A monoid is a type M for which there exists an associative binary operation (M, M) => M and an identity I under this operation, such that mplus(m, I) == m == mplus(I, m) for all m of type M
Q. What is |+|?
This is just scalaz shorthand (or ASCII madness, ymmv) for the mplus binary operation
Q. What is ~?
It is a unary operator meaning "or identity" which is retrofitted (using scala's implicit conversions) by the scalaz library onto Option[M] if M is a monoid. Obviously a non-empty option returns its contents; an empty option is replaced by the monoid's identity.
Q. What is asMA.sum?
A Foldable is basically a datastructure which can be folded over (like foldLeft, for example). Recall that foldLeft takes a seed value and an operation to compose successive computations. In the case of summing a monoid, the seed value is the identity I and the operation is mplus. You can hence call asMA.sum on a Foldable[M : Monoid]. You might need to use asMA because of the name clash with the standard library's sum method.
Some References
Slides and Video of a talk I gave which gives practical examples of using monoids in the wild
def addOpts(xs: Option[Int]*) = xs.flatten.sum
This will work for any number of inputs.
If they both default to 0 you don't need pattern matching:
def addOpt(a:Option[Int], b:Option[Int]) = {
a.getOrElse(0) + b.getOrElse(0)
}
(Repeating comment above in an answer as requested)
You don't extract the content of the option the proper way. When you match with case Some(x), x is the value inside the option(type Int) and you don't call get on that. Just do
case Some(x) => x
Anyway, if you want content or default, a.getOrElse(0) is more convenient
def addOpt(ao: Option[Int], bo: Option[Int]) =
for {
a <- ao
b <- bo
} yield a + b